TY - GEN
T1 - The gendered geography of contributions to OpenStreetMap
T2 - 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019
AU - Das, Maitraye
AU - Hecht, Brent
AU - Gergle, Darren
N1 - Funding Information:
This work was supported in part by NSF grants 1815507, 1707296, and 1707319. We would like to thank Dana Choi and Oliver Baldwin for their help in the gender inference procedure. We would also like to thank Isaac Johnson for providing resources on OSM data processing and insightful feedback on the paper.
Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/5/2
Y1 - 2019/5/2
N2 - Millions of people worldwide contribute content to peer production repositories that serve human information needs and provide vital world knowledge to prominent artifcial intelligence systems. Yet, extreme gender participation disparities exist in which men signifcantly outnumber women. A central concern has been that due to self-focus bias [46], these disparities can lead to corresponding gender content disparities, in which content of interest to men is better represented than content of interest to women. This paper investigates the relationship between participation and content disparities in OpenStreetMap. We replicate fndings that women are dramatically under-represented as OSM contributors, and observe that men and women contribute diferent types of content and do so about diferent places. However, the character of these diferences confound simple narratives about self-focus bias: we fnd that on a proportional basis, men produced a higher proportion of contributions in feminized spaces compared to women, while women produced a higher proportion of contributions in masculinized spaces compared to men. We discuss the implications of these complex results for both theory and practice.
AB - Millions of people worldwide contribute content to peer production repositories that serve human information needs and provide vital world knowledge to prominent artifcial intelligence systems. Yet, extreme gender participation disparities exist in which men signifcantly outnumber women. A central concern has been that due to self-focus bias [46], these disparities can lead to corresponding gender content disparities, in which content of interest to men is better represented than content of interest to women. This paper investigates the relationship between participation and content disparities in OpenStreetMap. We replicate fndings that women are dramatically under-represented as OSM contributors, and observe that men and women contribute diferent types of content and do so about diferent places. However, the character of these diferences confound simple narratives about self-focus bias: we fnd that on a proportional basis, men produced a higher proportion of contributions in feminized spaces compared to women, while women produced a higher proportion of contributions in masculinized spaces compared to men. We discuss the implications of these complex results for both theory and practice.
KW - Gender
KW - OpenStreetMap
KW - Peer production
KW - Rural
KW - Self-focus bias
KW - Urban
UR - http://www.scopus.com/inward/record.url?scp=85067628982&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067628982&partnerID=8YFLogxK
U2 - 10.1145/3290605.3300793
DO - 10.1145/3290605.3300793
M3 - Conference contribution
AN - SCOPUS:85067628982
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 4 May 2019 through 9 May 2019
ER -
